Restraint management

ABSTRACT

There is provided a restraint management apparatus. The restraint management apparatus comprises a processing unit arranged to: receive one or more types of sensor data; determine a status of a subject based on the received sensor data; determine, based on the determined subject status, a restraint parameter for a restraint device configured to restrain a body part of the subject; and output a signal based on the determined restraint parameter.

TECHNICAL FIELD OF THE INVENTION

The invention relates to a restraint management apparatus and method foruse in restraining a subject, and in particular relates to a restraintmanagement apparatus and method for use in conjunction with a medicalrestraint system.

BACKGROUND TO THE INVENTION

In clinical environments such as hospitals and care homes, it issometimes necessary to restrain a subject, e.g. by fixating them totheir bed by means of restraining straps or the like. Use of suchrestraints may be required, for example, when patients (subjects) becomevery active due to a certain disease (e.g. one which causes delirium),such that they risk injuring themselves or dislodging or damagingmedical equipment such as IV lines, endotracheal tubes or feeding tubes.Some subjects may not be permitted to get out of bed without assistance,for instance because they are connected to medical equipment and/orbecause they are at a high risk of falling over if they attempt to doso. It is therefore an important patient safety issue to restraincertain subjects when necessary. Currently, restraining straps areapplied manually by medical staff. However; with current systemschanging restraint parameters such as range/length (i.e. the freedom ofmovement the restraining straps permit the subject) requires manualintervention by a caregiver, and this means that the restraintparameters are normally kept the same for the whole period during whichthe restraints are in place.

Decisions about when to apply/release restraints for a given patient aremade by medical staff based on their observations. However; it isgenerally not possible for medical staff to observe every subject intheir care, all of the time. This means that there are times when asubject's restraint status is not appropriate to their current condition(e.g. they remain restrained even when lying quietly, they are notrestrained whilst moving violently, they are restrained with too greator too little freedom of movement for their current condition).

There is therefore a need for a system which can reduce the amount oftime for which a subject is inappropriately restrained. Preferably sucha system would be able to achieve a more optimal balance between theclinical need to ensure the safety of the subject and the subject's needto be comfortable and free to move.

SUMMARY OF THE INVENTION

According to a first aspect of the invention, there is provided arestraint management apparatus. The restraint management apparatuscomprises a processing unit arranged to: receive one or more types ofsensor data; determine a status of a subject based on the receivedsensor data; determine, based on the determined subject status, arestraint parameter for a restraint device configured to restrain a bodypart of the subject; and output a signal based on the determinedrestraint parameter.

Thus, embodiments of the invention advantageously provide an automaticway to predict when a given subject should be restrained, released, orallowed more or less freedom of movement, based on the detectedcondition of the subject. This creates the possibility of automaticallyupdating restraint parameters in real time, in response to changes in asubject's condition. Thus, an optimum balance between the clinical needto ensure the safety of the subject and the subject's need to becomfortable and free to move can be achieved.

In some embodiments the processing unit is further arranged to receiveone or more types of non-sensor data relating to the subject. In somesuch embodiments the processing unit is arranged to determine a statusof a subject based additionally on the received non-sensor data. In someembodiments the one or more types of non-sensor data comprises dataoriginating from a caregiver. In some such embodiments the one or moretypes of non-sensor data comprises data manually input by a caregiver tothe restraint management apparatus or to a device in communication withthe restraint management apparatus.

In some embodiments the processing unit comprises a memory containingone or more predefined signatures, each predefined signature relating toa particular type of feature. In some such embodiments the processingunit is arranged to determine a status of a subject by comparing thereceived data to the one or more predefined signatures to detect one ormore features in the received sensor data.

In some embodiments the processing unit is arranged to determine astatus of a subject by determining one or more of: a physiologicalcondition of the subject, a position of the subject; a position of abody part of the subject; a movement level of a body part of thesubject; an activity level of the subject; whether the subject is asleepor awake; whether the subject's eyes are open; whether the subject isdelirious; whether movement of a body part of the subject meets apredefined criterion; whether movement of the subject meets a predefinedcriterion.

In some embodiments the processing unit is arranged to determine astatus of a subject such that the determined status comprises a statusvalue for one or more factors. In some such embodiments status valuecomprises one or more of: a descriptive indication; a numerical score; anon-numerical level indication.

In some embodiments the processing unit comprises a memory containingrules relating subject status values to restraint parameters. In somesuch embodiments the processing unit is arranged to determine arestraint parameter by applying one or more of the rules to thedetermined subject status value. In some such embodiments the processingunit comprises a machine learning module and the rules have beengenerated by the machine learning module based on historical datarelating to the subject. In some embodiments the processing unit isarranged to receive a restraint parameter which has been manually-inputto a restraint device, and the machine learning module is arranged toupdate the generated rules based on the received manually-inputrestraint parameter.

In some embodiments the processing unit is arranged to determine arestraint parameter such that the determined restraint parametercomprises one of: activation of a restraint device; inactivation of arestraint device; activation of a given restraining component of arestraint device; inactivation of a given restraining component of arestraint device; tightness of a given restraining component of arestraint device; length of a given restraining component of a restraintdevice; duration of activation of a restraint device; duration ofactivation of a given restraining component of a restraint device.

In some embodiments the processing unit is arranged to output a signalcomprising one or more of: a control signal to an automated restraintdevice arranged to cause the automated restraint device to apply thedetermined restraint parameter; a signal to a device associated with acaregiver, the signal comprising an instruction to the caregiver toimplement the determined restraint parameter; a control signal to analarm module of the restraint management apparatus arranged to cause thealarm module to generate an alarm in dependence on the determinedrestraint parameter; a control signal to a display module of therestraint management apparatus arranged to cause the display module todisplay information in dependence on the determined restraint parameter;a control signal to a subject feedback module arranged to cause thesubject feedback module to generate a message to the subject; a controlsignal to a lighting module arranged to cause the lighting module toactivate a light. In some embodiments the processing unit is arranged tooutput the signal after a predefined amount of time has passed since theprocessing unit last output a signal of the same type as the signal.

The invention also provides, according to a second aspect, a restraintsystem. The restraint system comprises a restraint management apparatusaccording to the first aspect; and a restraint device configured torestrain a body part of a subject. The restraint device is arranged to:receive a signal output by the restraint management apparatus, and inresponse to a signal received from the restraint management apparatus,apply a restraint to the subject or alter a parameter of a restraintapplied to the subject.

In some embodiments the restraint device is further arranged to: receivea manually-input restraint parameter; in response in response to asignal received from the restraint management apparatus, apply arestraint to the subject or alter a parameter of a restraint applied tothe subject; and transmit a signal containing the manually-inputrestraint parameter to the restraint management apparatus.

The invention also provides, according to a third aspect, a method foruse in restraining a subject. The method comprises: receiving one ormore types of sensor data; determining a status of a subject based onthe received sensor data; and determining, based on the determinedsubject status, a restraint parameter for a restraint device configuredto restrain a body part of the subject.

In some embodiments the received sensor data comprises one or more of:an image including a subject; an image including a subject and one ormore objects in the vicinity of the subject; audio data including soundsgenerated by a subject; accelerometer data obtained by an accelerometerworn by a subject; measurements of one or more physiologicalcharacteristics of a subject; restraint-related data obtained by asensor associated with a restraint device; pressure data obtained by abed sensor; bed rail position data obtained by a bed rail sensor.

In some embodiments the received sensor data comprises an imageincluding a subject and one or more objects. In some such embodimentsdetermining a status of a subject comprises: determining a position of abody part of the subject; determining a position of an object in theimage; calculating a distance between the body part and the object; andcomparing the calculated distance to a predetermined threshold.

BRIEF DESCRIPTION OF THE DRAWINGS

For a better understanding of the invention, and to show more clearlyhow it may be carried into effect, reference will now be made, by way ofexample only, to the accompanying drawings, in which:

FIG. 1 is an illustration of a restraint management apparatus accordingto a general embodiment of the invention;

FIG. 2 is a flow chart illustrating a method for use in restraining asubject according to a general embodiment of the invention; and

FIG. 3 is an illustration of an example restraint device for use with arestraint management apparatus according to the invention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

FIG. 1 shows a restraint management apparatus 10 according to anembodiment of the invention. The restraint management apparatus 10 isfor use with a restraint device 14 configured to restrain a body part ofa subject. In embodiments the restraint device 14 is configured toprovide a controllable resistance to movement of a body part. Therestraint management apparatus 10 comprises a processing unit. In someembodiments the restraint management apparatus also comprises one ormore functional modules, e.g. an alarm module, a display module, acommunications module, a user input module, a subject feedback module topresent messages to the subject (e.g. audio or text messages), alighting module to illuminate the subject and/or their surroundings,etc. The processing unit of the restraint management apparatus 10 isarranged to receive one or more types of sensor data 16. In someembodiments the processing unit is arranged to receive sensor data 16from one or more sensor devices 18. Each sensor device 18 can be, e.g.,a camera, microphone, accelerometer, medical monitoring device, or anyother type of sensor device arranged to collect sensor data relating toa subject. In some embodiments the processing unit is arranged toreceive sensor data from the restraint device 14. In some embodimentsthe processing unit is arranged to receive sensor data from a user inputmodule of the restraint management apparatus (e.g. where a caregiver hasmanually input readings obtained by a sensor), and/or a communicationsmodule of the restraint management apparatus (e.g. where sensor data issent to the restraint management apparatus from a remote electronicdevice, such as a laptop or smartphone of a caregiver). In someembodiments the processing unit is arranged to receive sensor data inreal time. In alternative embodiments the processing unit is arranged toreceive sensor data at periodic intervals, e.g. in response to a requestsent from the processing unit to a sensor device 18 or the restraintdevice 14.

In some embodiments the processing unit is further arranged to receivenon-sensor data, which may or may not be related to the subject.Subject-related non-sensor data can comprise, for example, historicalsubject information, medical test results, diagnoses, etc. Non-subjectrelated non-sensor data can comprise, for example, software updates,information relating to a restraint device, or any other type ofinformation/data that may be used by the restraint management apparatus.In some embodiments the non-sensor data comprises a manually-inputrestraint parameter which has been input to a restraint device by acaregiver. It will be appreciated that manually-input data comprises anydata received by a device which originates from a caregiver or otherhuman. Manually-input data can, but need not, be input via an inputinterface of the device receiving the data. Manually-input data can alsobe input via a remote device in communication with the device receivingthe data. Non-sensor data may be received in any of the mannersdescribed above in relation to the sensor data.

The processing unit is further arranged to determine a status of asubject based on the received sensor data (and, in some embodiments,received non-sensor data). The determined status should be related tothe restraint requirements of the subject, and will generally thereforebe indicative of a current or expected amount/type of activity/movementof the subject. In some embodiments the processing unit is arranged todetermine a status of a subject by determining one or more of: aphysiological condition of the subject, a position of the subject; aposition of a body part of the subject; a movement level of a body partof the subject; an activity level of the subject; whether the subject isasleep or awake; whether the subject's eyes are open; whether thesubject is delirious; whether movement of a body part of the subjectmeets a predefined criterion (e.g. defined such that only unusualmovement will meet the criterion); whether movement of the subject meetsa predefined criterion (e.g. defined such that only unusual movementwill meet the criterion).

Various techniques for extracting physiological, position and/oractivity information from sensor data are known in the art. For example,data from an accelerometer mounted on the subject, and/or from apressure sensor mounted on their hospital bed can be analyzed todetermine the position of a subject and/or whether and to what extentthe subject is moving. Subject movement can also be determined fromimage data acquired by a camera, using video analysis techniques. Imagedata can be used to determine the proximity of a body part of a subjectto a medical device or other object (e.g. a wall, bed rail, item offurniture, etc.) Audio data collected by a microphone can detectvocalizations, movement noises and/or impact noises generated by thepatient, which can be used to determine whether they are in distress,likely to attempt to get out of bed, and/or are at risk of harming themself. Physiological data (e.g. heart rate, respiration rate, breathingpattern, ECG data) can be used in the determination of the status of asubject, e.g. by indicating whether the subject is asleep or awake,indicating which sleep stage the subject is in, and/or indicatingwhether they are experiencing increased circulatory effort (which canresult from increased activity).

In some embodiments the processing unit is arranged to determine thestatus of a subject by detecting patterns and/or features in thereceived sensor data. For example, in some embodiments signatures and/orpatterns associated with features of interest (such as a particular bodypart in an image of the subject; a particular object in an image of thesubject; a vocalization in an audio recording of the subject; an impactsound in an audio recording of the subject; a peak in accelerometerdata, etc.) are stored in a memory associated with the processing unit,and the processing unit is arranged to determine the status of a subjectby comparing detected patterns/features with the storedsignatures/patterns. In some embodiments the determination is performedbased on received sensor data from a particular instant in time (i.e.the determination uses a static analysis). In some embodiments thedetermination is performed using received sensor data covering a timeperiod (i.e. the determination uses a dynamic analysis). In someembodiments determining the status of a subject comprises tracking adetected feature over a time period. In some embodiments determining thestatus of a subject comprises detecting movement of a body part of thesubject. In some such embodiments, detected movements are classified asbeing one or more of several different predefined movement types. Anysuitable known signal analysis and feature extraction techniques may beused in the performance of step 202.

In a particular embodiment in which the received sensor data 16comprises image data containing the subject and their immediatesurroundings, the processing unit is arranged to determine the status ofthe subject by detecting, using image analysis techniques, the relativepositions of body parts of the subjects and objects. The detected bodyparts can comprise, for example, one or more of a hand, a foot, thehead, etc. The detected objects can comprise, for example, one or moreof a patient monitor, an IV stand, a bed rail, a bedside table, etc. Insome such embodiments the processing unit is arranged to calculatedistances between the detected body parts and the detected objects. Insome such embodiments the processing unit is arranged to compare thecalculated distances to a predefined threshold. The subject status maythen be determined in dependence on the result(s) of the comparing. Forexample, in some embodiments a status indicating that restraint of abody part is required will be determined only if the distance betweenthat body part and an object is less than the predefined threshold. Insome embodiments a status indicating that restraint of multiple or allbody parts is required will be determined if the distance between atleast one body part and an object is less than the predefined threshold.In further or alternative embodiments, the processing unit is arrangedto calculate the velocity of a detected body part towards a detectedobject (for example from a series of measurements of the relativepositions of body parts and objects obtained from a time series ofimages). In some such embodiments the processing unit is arranged tocompare the calculated velocity to a predefined velocity threshold. Thesubject status may then be determined in dependence on the result(s) ofthe comparing. For example, in some embodiments a status indicating thatrestraint of a body part is required will be determined only if thevelocity of the body part towards the object is more than the predefinedvelocity threshold. In some embodiments a status indicating thatrestraint of multiple or all body parts is required will be determinedif the velocity of at least one body part towards an object is more thanthe predefined velocity threshold. An exemplary velocity threshold couldbe 2 m/s.

In some embodiments (i.e. embodiments in which the processing unit isarranged to receive sensor data in real time) the processing unit isarranged to determine a status of a subject in real time or near realtime.

In some embodiments the determined subject status comprises a statusvalue (which may, for example, take the form of a descriptive indication(e.g. asleep with low activity, asleep with high activity, awake withlow activity, awake with high activity, delirious, violent, etc.) anumerical score (e.g. representing activity level), and/or anon-numerical status indication (e.g. a color corresponding to a low,medium or high risk that the patient will cause harm if not restrained).In some embodiments the determined subject status comprises a statusvalue in respect of each of multiple factors, where a factor could be,e.g., activity level, medical condition, sleep/wake state, lucidity,etc. In some embodiments the determined subject status is indicated,e.g. by the restraint management apparatus or a device in communicationwith the restraint management apparatus. In some such embodimentsindicating the determined subject status comprises displaying a messageor visual status indication. In some embodiments indicating thedetermined subject status comprises emitting light of a particularcolor.

The processing unit is further arranged to determine, based on thedetermined subject status, a restraint parameter for a restraint deviceconfigured to restrain a body part of the subject, e.g. the restraintdevice 14. The determined restraint parameter can comprise, for example,one or more of: activation/inactivation of the restraint device (i.e. asa whole), activation/inactivation of a given restraining component ofthe restraint device, tightness/length of a given restraining component,duration of activation of the restraint device or of a given restrainingcomponent, etc. In some embodiments the processing unit is provided witha set of rules/relationships (e.g. stored in a memory of the restraintmanagement device) relating restraint parameters to subject status andis arranged to use these rules/relationships in determining a restraintparameter. An example of such a rule could be, “if subjectstatus=excessive hand movement, set hand restraining components tomaximum tightness”.

In embodiments where the restraint device can provide a controllableresistance to movement of a body part, the restraint parameter canindicate a level of resistance to movement to be provided by therestraint device.

In some embodiments the processing unit is arranged to determine arestraint parameter by applying at least one predefined criterion to thedetermined subject status. In some embodiments the predefined criterioncomprises a set of conditions. In some embodiments the set of conditionscomprises a time-based condition and a value-based condition. Avalue-based condition is defined such that whether or not a status valuemeets the condition depends on the value itself. A time-based condition,on the other hand, specifies a condition (e.g. a minimum) relating tothe amount of time for which the status information has consistently meta value-based condition. Providing a time-based condition can beadvantageous because some status factors may need to be consistentlypresent for a duration of time before they can be considered to reliablyindicate that a change in a restraint parameter (e.g. application of therestraint device to a currently unrestrained subject) is required. Insome embodiments the set of conditions comprises a plurality ofvalue-based conditions.

In some embodiments the processing unit is arranged to determine arestraint parameter using a function of the distance from a body part toan object in the environment, and/or of the velocity of a body parttowards an object in the environment. An exemplary function based ondistance x is set out below:

x ≦ BT F_(r) = F_(max) x > RT F_(r) = F_(min) Otherwise F_(r) =F_(max) + (BT − x)/(RT − BT) · (F_(max) − F_(min))where BT is a blocking threshold distance at which the movement of thebody part is to be blocked (i.e. a maximum restraining force, F_(max),is to be applied), RT is a restraining threshold distance beyond which aminimum restraining force (F_(min)) is to be applied. This functionleads to the restraining force increasing from the minimum force atdistances greater than RT up to the maximum force at distances of BT orless. An exemplary value for F_(max) can be 1000 Newton (N), althoughany force that would prevent movement of the body part can be used. Anexemplary value for F_(min) can be 0.1 N, although any force that wouldallow free or reasonably free movement of the body part can be used. Anexemplary value for BT can be 10 centimeters, and an exemplary value forRT can be 25 cm. The restraining force provided by the above functioncan be related to a restraint parameter. It will be appreciated that theabove function is merely exemplary, and those skilled in the art will beaware of other types or forms of functions that can be used to relatedistance and/or velocity to a restraining force.

In embodiments where the subject status comprises a status value foreach of multiple factors, the at least one predefined criterion may befactor-specific. For example, in some embodiments the determined subjectstatus comprises a status value for the factor “sleep/wake state” and astatus value for the factor “activity level”. In some such embodimentsthe processing unit is arranged to determine a restraint parameter basedon both whether the sleep/wake state value is equal to a predefinedvalue and whether the activity level value exceeds a predefinedthreshold. For example, in some such embodiments if the sleep/wakestatus value is “asleep” and the activity level is “medium” then theprocessing unit will determine that the restraining device should beused, but if the sleep/wake status value is “awake” and the activitylevel is “medium” then the processing unit will determine that therestraining device should not be used.

In some embodiments the processing unit includes a machine learningmodule, configured to use standard machine learning techniques toidentify or generate rules, relationships, etc. relating restraintparameters to subject status. In some such embodiments the machinelearning module is configured to apply machine learning techniques tohistorical data, e.g. historical subject status data, historicalphysiological measurement data, and/or historical restraint information(e.g. information about restraint parameters used and/or theirappropriateness). In some embodiments (i.e. embodiments in which theprocessing unit is arranged to receive manually-input restraintparameters from the restraint device 14), the machine learning module isconfigured to generate rules/relationships relating restraint parametersto subject status based on manually-input restraint parameters receivedfrom the restraint apparatus. In some such embodiments the machinelearning module is arranged to update existing rules/relationships basedon manually-input restraint parameters received from the restraintapparatus. In some such embodiments the processing unit 12 is arrangedto determine a restraint parameter based on rules or relationshipsgenerated or identified by the machine learning module.

In preferred embodiments the processing unit is arranged to determine arestraint parameter in real time or near real time. Advantageously thisfeature can prevent inappropriate restraint of a subject, and minimizethe amount of time for which a subject is restrained. Conversely, it canensure that restraint is applied rapidly when required, reducing therisk of harm to the subject.

The processing unit is further arranged to output a signal 12 based onthe determined restraint parameter. In some embodiments the signal 12comprises a control signal, and is output to the restraint device 14,e.g. by a communications module of the restraint management apparatus10. In some such embodiments the signal 12 causes the restraint deviceto apply the determined restraint parameter. For example, in one exampleembodiment in which the determined restraint parameter comprises aspecified length of a given restraint component of the restraint device14, the output signal 12 comprises a control signal which causes therestraint device 14 to set the length of the given restraint componentto be the specified length. In another example embodiment in which thedetermined restraint parameter indicates a level of resistance tomovement to be provided by the restraint device 14, the output signal 12comprises a control signal which causes the restraint device 14 to setthe resistance to movement to the specified level of resistance. In someembodiments in which the signal 12 is output to the restraint device 14,the signal 12 is arranged to cause the restraint device 14 to displaythe determined restraint parameter, e.g. on a display associated withthe restraint device 14. In some embodiments the signal comprises aninstruction to a caregiver to implement the determined restraintparameter.

In some embodiments the signal comprises a control signal arranged tocause a message to be presented to the subject. Such a message couldprovide the subject with instructions and/or reassurance. A suitablemessage could say, for example, “Please calm down. A nurse will be withyou shortly”. In some embodiments the message to the subject comprisesan audio message, e.g. generated by a loudspeaker comprised in or incommunication with the restraint management device 10. In someembodiments the message to the subject comprises a visual message, e.g.displayed by a display comprised in or in communication with therestraint management device 10.

In some embodiments the processing unit is arranged to output the signal12 after a predefined amount of time has passed since the processingunit last output a signal of the same type as the current signal 12(e.g. in some embodiments an instruction or control signal arranged tocause adjustment of a particular restraint would comprise a first typeof signal, and an instruction or control signal arranged to causeadjustment of a different restraint, a control signal arranged togenerate an alarm, a warning message to a caregiver, etc. would each beconsidered to be a signal of a different type to the first signal). Thiscan reduce the stress experienced by the subject, since if restraintparameters are changed too often this can confuse or surprise thesubject.

In some embodiments the signal 12 comprises a control signal and is sentto a functional module of the restraint management apparatus 10. In suchembodiments the control signal may be arranged, for example, to causeone or more of:

an alarm module to generate an alarm;a subject feedback module to generate a message to the subject;a communications module to generate a message to a caregiver;a communications module to send a signal to a remote device;a communications module to send a signal to the restraint managementapparatus;a display module to display information;a lighting module to activate a light.

In some embodiments the processing unit is arranged to output aplurality of signals, for example a control signal to the restraintdevice 14 and a control signal to an alarm module of the restraintmanagement apparatus 10 causing it to generate an alarm. In someembodiments the processing unit is arranged to output a signal 12continuously, in real-time or near real-time. In some embodiments theprocessing unit is arranged to output a signal in response to a changein the determined parameter. In some embodiments the processing unit isarranged to output a signal 12 at periodic intervals.

The restraint device 14 can be any device arranged to restrain (i.e. torestrict the movement of) a body part of a subject. In some embodimentsthe restraint device 14 comprises multiple restraint components, each ofwhich is arranged to restrain a particular body part. In some suchembodiments, the restraint components comprise one or more straps (e.g.wrist straps, ankle straps, a waist strap, etc.). In some embodimentsthe restraint components comprise one or more tethers. In someembodiments the restraint device 14 comprises one or more bed rails. Insome embodiments the restraint device 14 comprises a bed sheet or coverwhich can be adjustably tightened over the subject. In some embodimentsthe restraint device is attached to or integrated in a hospital bed.Preferably the restraint device 14 is arranged such that one or morerestraint parameters (e.g. strap tightness/length, tether length, bedrail height, resistance to movement) are adjustable during use of therestraint device 14. Preferably, the restraint device is arranged to beas user friendly as possible. For example, straps can comprise a softand/or padded material. Straps and/or tethers may be arranged to varythe resistance to movement in dependence on the length/tightness forvariable fixation ranges. This can advantageously achieve a subtlebraking of a moving body part rather than a hard stop, which can reducethe stress felt by the subject as a result of being restrained.

In some embodiments the restraint device 14 includes at least one sensorfor acquiring sensor data. In some embodiments the restraint device 14includes at least one sensor associated with each restraint component ofthe restraint device 14. The at least one sensor can comprise, forexample, a strain gauge; an accelerometer; a position sensor. In someembodiments the restraint device 14 includes a sensor arranged to detecta parameter of the subject (e.g. position of a given body part, movementof a given body part, etc.). In some embodiments the restraint device 14includes a sensor arranged to detect a parameter of the restraint device(e.g. position of a bed rail; length of a strap; tension in astrap/tether; whether or not a given restraint component is in use;etc.). In some embodiments in which the restraint device 14 includes atleast one sensor, the restraint device 14 is arranged to output sensordata, e.g. to the restraint management apparatus 10 or to another remotedevice (such as a patient monitoring device or a hospital computersystem).

The restraint device 14 can be an automated restraint device or amanually operated restraint device. A manually operated restraint devicerequires a human operator to adjust its restraint parameters. Inembodiments where the restraint management device 10 is used inconjunction with a manually operated restraint device, the restraintmanagement device is arranged to alert a caregiver to a change in thedetermined restraint parameter, so that the caregiver can implement thenewly determined parameter. Although caregiver intervention to adjustthe restraint device is still required, in such situations the restraintmanagement system significantly reduces the burden on caregivers byreducing or removing the need for a caregiver to continuously monitorthe status of subject.

An automated restraint device, on the other hand, is able to adjust oneor more of its restraint parameters without input from a human operator,e.g. in response to a control signal received from the restraintmanagement apparatus 10. Advantageously, the use of an automatedrestraint device in conjunction with a restraint management apparatusaccording to embodiments of the invention can enable the rapid(preferably real-time) adjustment of the nature and degree of restraintapplied to a given subject, based on their current status. This cansignificantly reduce or even eliminate periods of inappropriaterestraint. Preferably an automated restraint device is arranged suchthat restraint parameters can also be adjusted manually, e.g. via a userinterface of the restraint device. In some embodiments, an automatedrestraint device is arranged such that a caregiver is required toapprove/confirm a restraint parameter generated by the restraintmanagement apparatus before the automated restraint device will applythat parameter. In some such embodiments the approval can be doneremotely, via a device (such as a nurses' station, or portableelectronic device of a caregiver) which is in communication with therestraint management apparatus and the restraint device.

FIG. 2 shows an example of a method for use in restraining a subject,which can be implemented by the restraint management apparatus 10. In afirst step 201 sensor data 16 is received, e.g. from one or more sensordevices, from a restraint device, from a user input module of therestraint management apparatus 10, from a remote electronic device, etc.In some embodiments the sensor data is received as a continuous stream.In some embodiments the sensor data is received periodically. In someembodiments the sensor data is received in response to a requestpreviously sent to a sensor device/restraint device. In some embodimentsthe sensor data has been time-stamped at the time of its generation. Insome embodiments the sensor data is time-stamped at the time of itsreceipt, e.g. by the processing unit of the restraint managementapparatus 10. In some embodiments the received sensor data directlyrelates to a subject, in that it comprises measurements of aphysiological characteristic of that subject. In some embodiments thereceived sensor data indirectly relates to a subject. For example, datawhich indirectly relates to a subject could comprise an image or audiorecording of the subject's hospital room which includes the subject aswell as their surroundings. In some embodiments the received sensor datais stored, e.g. in a memory of the restraint management apparatus 10.

In some embodiments an optional step 202 of receiving non-sensor datarelating to the subject, e.g. from a user input module of the restraintmanagement apparatus, a remote electronic device, etc. is performed. Thesubject-related non-sensor data can comprise, e.g. test results; amedical diagnosis; historical physiological characteristic data;clinical outcome data; treatment data, restraint data, etc. In someembodiments the received subject-related non-sensor data is stored, e.g.in a memory of the restraint management apparatus 10.

In step 203 a status of a subject (i.e. the subject to which thereceived sensor data either directly or indirectly relates) isdetermined based on the received sensor data, e.g. by the processingunit of the restraint management apparatus 10. In embodiments in whichsubject-related non-sensor data is received, a status of the subject isdetermined based additionally on the non-sensor data. In some suchembodiments the received sensor data and the received non-sensor dataare combined by a data fusion module of the processing unit of therestraint management apparatus 10. In some embodiments the combiningcomprises assigning one or more weights to the received sensor data andthe received non-sensor data. For example, non-sensor data in the formof data input manually by a caregiver may be assigned a higher weightthan sensor data. In some embodiments the non-sensor data can comprise asubject status manually input by a caregiver. In some such embodimentsthe performance of step 203 may comprise ignoring the received sensordata and determining the subject status to be the subject statusreceived as non-sensor data. In some embodiments rules, e.g. generatedby the machine learning module of the processing unit, are used in thecombining. The determined subject status may take any of the formsdescribed above in relation to the processing unit of the restraintmanagement apparatus 10. Likewise, determining a status of a subject cancomprise any of the processing techniques described above in relation tothe processing unit of the restraint management apparatus 10.

In step 204 a restraint parameter is determined based on the determinedsubject status. The determined restraint parameter may take any of theforms described above in relation to the processing unit of therestraint management apparatus 10 or in relation to the restraint device14. Likewise, determining a restraint parameter can comprise any of theprocessing techniques described above in relation to the processing unitof the restraint management apparatus. It is generally expected that amain consideration in the determining of a restraint parameter will beto maintain a balance between the comfort and freedom of the subject,and the clinical need to prevent certain adverse events occurring. Thedetermined restraint parameter may be output in any suitable manner(including any of the manners described above in relation to the outputsignal 12) such that it can be implemented in restraining (or releasing)the subject.

In some embodiments the method includes the optional additional step 205of applying a restraint device to the subject in accordance with thedetermined restraint parameter. The restraint device can have any or allof the features described above in relation to the restraint device 14.In some embodiments applying the restraint device comprises a caregivermanually setting a parameter of the restraint device to be equal to thedetermined parameter. In some embodiments applying the restraint devicereceiving a control signal based on a determined restraint parameter,and in response to the control signal, setting a parameter of itsoperation/configuration to be equal to the determined parameter.

FIG. 3 shows a specific example of an automated restraint device 30 foruse with a restraint management apparatus according to the invention.The restraint device 30 comprises various restraint components arrangedon a hospital bed 31, and a control unit 32 which is in communication(either wired or wireless) with the restraint components so as to beable to send control signals to each of the restraint components. Therestraint components comprise a pair of bed rails 33, the height ofwhich can be adjusted in response to a control signal from the controlunit 32 (e.g. by means of any suitable actuator). The restraintcomponents also comprise a pair of wrist cuffs 34, each of which isconnected to the hospital bed 31 by a tether 35. Similarly, therestraint components also comprise a pair of ankle cuffs 36, each ofwhich is connected to the hospital bed 31 by a tether 37. The tightnessof the wrist and ankle cuffs is manually adjustable (although it will beappreciated that embodiments are possible in which the tightness of thewrist and/or ankle cuffs can be automatically adjusted in response to acontrol signal from the control unit 32, e.g. by means of any suitableactuator). The length of each wrist and ankle tethers is individuallyand automatically adjustable in response to a control signal from thecontrol unit 32, e.g. by means of any suitable actuator. The restraintcomponents also comprise a waist strap 38. The waist strap 38 isarranged to be manually applied (although it will be appreciated thatembodiments are possible in which the waist strap can be automaticallyapplied) but once applied can be tightened automatically in response toa control signal from the control unit 32.

Where the restraint device is to provide a subtle braking of a movingbody part rather than a hard stop as described above, the restraintcomponents can comprise, e.g. a wrist strap, with one end of a connectorstring or cord attached thereto, and the other end attached to a spoolinside a restraint actuator. The restraint actuator controls the freedomof movement of the spool, e.g. using a braking system (known to thoseskilled in the art of e.g. mechatronics). Depending on the configurationof the actuator system, the applied braking force can be proportional tothe effective restraining force in the string or cord. The brakingsystem may include a force sensor for force feedback control. In someembodiments, in the case of using a braking system as the main actuator,it can be important to maintain a minimal restraining force (e.g.F_(min)) in the string or cord at all times, to avoid slacking andtangling. This can be realized using a simple spring connected to thespool. Those skilled in the art will be aware of various types ofrestraint components that can be used to provide subtle braking of amoving body part.

The restraint device 30 further comprises a plurality of sensors (notshown) which are in communication (wired or wireless) with the controlunit 32 and are arranged to send data to the control unit 32. Thesensors comprise an accelerometer attached to each wrist cuff 34 andankle cuff 36, a plurality of pressure sensors distributed over the baseof the hospital bed 31, a position sensor attached to each bed rail 33,and a strain gauge attached to each tether 35, 37. The control unit isin communication with a restraint management apparatus (e.g. therestraint management apparatus 10 of FIG. 1) and is arranged to senddata received from the plurality of sensors to the restraint managementapparatus. In this embodiment the restraint management apparatus isprovided a separate device to the restraint device, however; alternativeembodiments are envisaged in which the restraint management apparatus isprovided as a module of the control unit 32.

The control unit 32 is arranged to receive a control signal output by arestraint management apparatus, where the control signal is arranged tocause the restraint device to implement one or more restraint parametersdetermined by the restraint management apparatus. The control unit isarranged to, in response to receiving the control signal, implement adetermined restraint parameter by sending a control signal to arestraint component arranged to cause an operational parameter of thatrestraint component to become equal to the determined restraintparameter. For example, in a case where the determined restraintparameter is “wrist tethers=50 cm”, the control unit 32 sends a controlsignal to each of the wrist tethers 35, the control signal beingarranged to cause an actuator associated with each of the wrist tethersto adjust the tether length to be equal to 50 cm.

The control unit 32 further comprises a user interface, via whichrestraint parameters can be manually input by a caregiver. The controlunit 32 is arranged to, in response to receiving a manually-inputrestraint parameter, implement the manually-input restraint parameter bysending a control signal to a restraint component arranged to cause anoperational parameter of that restraint component to become equal to themanually-input restraint parameter. The control unit 32 is also arrangedto send the manually-input restraint parameter to the restraintmanagement apparatus, e.g. for use by the restraint management apparatusin generating or updating rules/relationships relating subject status torestraint parameters, as described above in relation to FIG. 1. Thecontrol unit 32 is arranged to wait for a predetermined amount of timebefore implementing a change to an operating parameter of a givenrestraint component. In some embodiments the predetermined waiting timemay be longer if the last change was performed to implement amanually-input restraint parameter than if the last change was performedto implement a restraint parameter determined by the restraintmanagement apparatus. In some embodiments the control unit is arrangedsuch that a manual input overrides signals received from the restraintmanagement apparatus for a predetermined period of time.

Embodiments of the invention therefore advantageously enable the amountof time for which a subject is inappropriately restrained to be reduced,whilst also enabling restraints to be applied rapidly in response topotentially harmful movements by the subject, thus reducing their riskof harming them self, other people, or medical equipment. Embodiments ofthe invention can facilitate automatic restraint implementation andadjustment, and therefore also have the potential to significantlyreduce the burden on caregivers, by reducing or eliminating therequirement for caregiver involvement in both monitoring a subject andadjusting restraint devices.

While the invention has been illustrated and described in detail in thedrawings and foregoing description, such illustration and descriptionare to be considered illustrative or exemplary and not restrictive; theinvention is not limited to the disclosed embodiments. Variations to thedisclosed embodiments can be understood and effected by those skilled inthe art in practicing the claimed invention, from a study of thedrawings, the disclosure and the appended claims. In the claims, theword “comprising” does not exclude other elements or steps, and theindefinite article “a” or “an” does not exclude a plurality. A singleprocessor or other unit may fulfil the functions of several itemsrecited in the claims. The mere fact that certain measures are recitedin mutually different dependent claims does not indicate that acombination of these measures cannot be used to advantage. A computerprogram may be stored/distributed on a suitable medium, such as anoptical storage medium or a solid-state medium supplied together with oras part of other hardware, but may also be distributed in other forms,such as via the Internet or other wired or wireless telecommunicationsystems. Any reference signs in the claims should not be construed aslimiting the scope.

1. A restraint management apparatus comprising: a processing unitarranged to: receive one or more types of sensor data; determine astatus of a subject based on the received sensor data, wherein thestatus comprises a distance between a body part of the subject and aselected object in the environment around the subject and/or velocity ofa body part of the subject towards a selected object in the environmentaround the subject; determine, based on the determined subject status, arestraint parameter for a restraint device configured to restrain thebody part of the subject, wherein the restraint device is configured toprovide a resistance to movement of the body part, and wherein therestraint parameter indicates a level of resistance to movement to beprovided by the restraint device, and wherein the restraint parameter isdetermined such that the level of resistance to movement provided by therestraint device increases as the distance between the body part and theselected object decreases and/or as the velocity of the body parttowards the selected object increases; and output a signal based on thedetermined restraint parameter.
 2. The restraint management apparatus ofclaim 1, wherein the processing unit is further arranged to receive oneor more types of non-sensor data relating to the subject and todetermine a status of a subject based additionally on the receivednon-sensor data.
 3. A restraint management apparatus according to claim1, wherein the processing unit comprises a memory containing one or morepredefined signatures, each predefined signature relating to aparticular type of feature, and wherein the processing unit is arrangedto determine a status of a subject by comparing the received data to theone or more predefined signatures to detect one or more features in thereceived sensor data.
 4. A restraint management apparatus according toclaim 1, wherein the processing unit is arranged to determine a statusof a subject such that the determined status comprises a status valuefor one or more factors, wherein each status value comprises one or moreof: a descriptive indication; a numerical score; a non-numerical levelindication.
 5. A restraint management apparatus according to claim 4,wherein the processing unit comprises a memory containing rules relatingsubject status values to restraint parameters, and is arranged todetermine a restraint parameter by applying one or more of the rules tothe determined subject status value.
 6. A restraint management apparatusaccording to claim 5, wherein the processing unit comprises a machinelearning module, wherein the rules have been generated by the machinelearning module based on historical data relating to the subject,wherein the processing unit is arranged to receive a restraint parameterwhich has been manually-input to a restraint device, and wherein themachine learning module is arranged to update the generated rules basedon the received manually-input restraint parameter.
 7. A restraintmanagement apparatus according to claim 1, wherein the processing unitis arranged to determine a restraint parameter such that the determinedrestraint parameter comprises one of: activation of a restraint device;inactivation of a restraint device; activation of a given restrainingcomponent of a restraint device; inactivation of a given restrainingcomponent of a restraint device; tightness of a given restrainingcomponent of a restraint device; length of a given restraining componentof a restraint device; duration of activation of a restraint device;duration of activation of a given restraining component of a restraintdevice.
 8. A restraint management apparatus according to claim 1,wherein the processing unit is arranged to output a signal comprisingone or more of: a control signal to an automated restraint devicearranged to cause the automated restraint device to apply the determinedrestraint parameter; a signal to a device associated with a caregiver,the signal comprising an instruction to the caregiver to implement thedetermined restraint parameter; a control signal to an alarm module ofthe restraint management apparatus arranged to cause the alarm module togenerate an alarm in dependence on the determined restraint parameter; acontrol signal to a display module of the restraint management apparatusarranged to cause the display module to display information independence on the determined restraint parameter; a control signal to asubject feedback module arranged to cause the subject feedback module togenerate a message to the subject; a control signal to a lighting modulearranged to cause the lighting module to activate a light.
 9. Arestraint management apparatus according to claim 1, wherein theprocessing unit is arranged to output the signal after a predefinedamount of time has passed since the processing unit last output a signalof the same type as the signal.
 10. A restraint system comprising: arestraint management apparatus according to claim 1; and a restraintdevice configured to restrain a body part of a subject, wherein therestraint device is arranged to: receive a signal output by therestraint management apparatus, and in response to a signal receivedfrom the restraint management apparatus, apply a restraint to thesubject or alter a parameter of a restraint applied to the subject. 11.A restraint system according to claim 10, wherein the restraint deviceis further arranged to: receive a manually-input restraint parameter; inresponse in response to a signal received from the restraint managementapparatus, apply a restraint to the subject or alter a parameter of arestraint applied to the subject; and transmit a signal containing themanually-input restraint parameter to the restraint managementapparatus.
 12. A method for use in restraining a subject, the methodcomprising: receiving one or more types of sensor data; determining astatus of a subject based on the received sensor data, wherein thestatus comprises a distance between a body part of the subject and aselected object in the environment around the subject and/or velocity ofa body part of the subject towards a selected object in the environmentaround the subject; and determining, based on the determined subjectstatus, a restraint parameter for a restraint device configured torestrain the body part of the subject, wherein the restraint device isconfigured to provide a resistance to movement of the body part, andwherein the restraint parameter indicates a level of resistance tomovement to be provided by the restraint device, and wherein therestraint parameter is determined such that the level of resistance tomovement provided by the restraint device increases as the distancebetween the body part and the selected object decreases and/or as thevelocity of the body part towards the selected object increases.
 13. Amethod according to claim 12, wherein the received sensor data comprisesone or more of: an image including a subject; an image including asubject and one or more objects in the vicinity of the subject; audiodata including sounds generated by a subject; accelerometer dataobtained by an accelerometer worn by a subject; measurements of one ormore physiological characteristics of a subject; restraint-related dataobtained by a sensor associated with a restraint device; pressure dataobtained by a bed sensor; bed rail position data obtained by a bed railsensor.
 14. A method according to claim 12, wherein the received sensordata comprises an image including a subject and one or more objects, andwherein determining a status of a subject comprises: determining aposition of a body part of the subject; determining a position of anobject in the image; calculating a distance between the body part andthe object; and comparing the calculated distance to a predeterminedthreshold.
 15. A method according to claim 12, wherein the receivedsensor data comprises a series of images including a subject and one ormore objects, and wherein determining a status of a subject comprises:determining a position of a body part of the subject in each of theimages; determining a position of an object in each of the images;calculating a distance between the body part and the object in each ofthe images; calculating a velocity of the body part towards the objectfrom the calculated distances; and comparing the calculated velocity toa predetermined velocity threshold.